The shape of the utility or value function in stochastic multicriteria acceptability analysis

DOI10.1007/s00291-011-0244-5zbMath1282.91086OpenAlexW2060362698WikidataQ110125333 ScholiaQ110125333MaRDI QIDQ1929954

Risto Lahdelma, Pekka Salminen

Publication date: 10 January 2013

Published in: OR Spectrum (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00291-011-0244-5

zbMATH Keywords

simulationmulticriteria analysisdecision supportSMAA

Mathematics Subject Classification ID

Decision theory (91B06)

Related Items (8)

Scoring procedures for multiple criteria decision aiding with robust and stochastic ordinal regression ⋮ A participatory multi-criteria approach for power generation and transmission planning ⋮ Complementary judgment matrix method with imprecise information for multicriteria decision-making ⋮ Preferential reducts and constructs in robust multiple criteria ranking and sorting ⋮ Stochastic multi-attribute acceptability analysis with numerous alternatives ⋮ On generating utility functions in stochastic multicriteria acceptability analysis ⋮ Combining an extended SMAA-2 method with integer linear programming for task assignment of multi-UCAV under multiple uncertainties ⋮ Stochastic multicriteria acceptability analysis based on Choquet integral

Cites Work

• A survey on stochastic multicriteria acceptability analysis methods
• Implementing stochastic multicriteria acceptability analysis
• The use of the SMAA acceptability index in descriptive decision analysis
• Simulation techniques for the sensitivity analysis of multi-criteria decision models
• Pseudo-criteria versus linear utility function in stochastic multi-criteria acceptability analysis
• SMAA-2: Stochastic Multicriteria Acceptability Analysis for Group Decision Making
• Estimating the Impact of Uncertainty on a Deterministic Multiattribute Evaluation
• Determining the implementation order of a general plan by using a multicriteria method
• Use of Piecewise Linear Value Functions in Interactive Multicriteria Decision Support: A Monte Carlo Study
• Simplified approaches for multicriteria decision making under uncertainty
• Robustness of Additive Value Function Methods in MCDM
• A NEW MEASURE OF RANK CORRELATION

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